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Walking and Selected Subpopulations and Setting

Assessing Walking Behaviors of Selected Subpopulations

LE MASURIER, GUY C.1; BAUMAN, ADRIAN E.2; CORBIN, CHARLES B.3; KONOPACK, JAMES F.4; UMSTATTD, RENEE M.5; VAN EMMERIK, RICHARD E. A.6

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Medicine & Science in Sports & Exercise: July 2008 - Volume 40 - Issue 7 - p S594-S602
doi: 10.1249/MSS.0b013e31817c68b1
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Abstract

Most humans must ambulate if for no other reason than to move from place to place. However, walking behavior among humans demonstrates large variability (18,44). The extent to which people walk and the reasons for walking are influenced by many factors including age, physical abilities, and environment to name a few (45,25). Although it is unrealistic to deal with all of the unique subpopulations and their walking behaviors, this review focuses on the walking behaviors of specific subpopulations that are large, and in some cases growing, in our world: youth, older adults, and individuals with disabilities. Additionally, the challenges in assessing walking behaviors are addressed from the perspectives of each subpopulation as well as from an international perspective.

WALKING BEHAVIORS (ACTIVITY PATTERNS) OF YOUTH

Youth (children aged 5-12 and adolescents aged 13-18) represent one of the most physically active subpopulation of humans. This elevated activity during youth is also true of other species. Children's physical activity (PA) is characterized by intermittent bouts at various intensities interspersed with periods of rest (3). As children move into adolescence, fewer bouts of vigorous and moderate-intensity PA are observed (42-44). Regardless of age, youth walking behaviors have not been well studied as researchers have focused on assessing intensity of activity without identifying the specific type of activity (e.g., walking, running, jumping). However, a recent study on children demonstrated that walking to school is associated with higher levels of overall PA compared with those who travel to school by motorized transport (13).

Existing PA guidelines acknowledge the intermittent and varied nature of youth PA. Current recommendations suggest that youth accumulate at least 60 min or more of daily moderate-to-vigorous-intensity PA, which is developmentally appropriate, enjoyable, and involves a variety of activities on all days of the week (32,34,41). More than 60 min up to several hours per day (32) is appropriate for youth and may be necessary to provide all of the diverse needs of this population (i.e., physical, social, and psychological needs for growth and development). Additionally, it is recommended that youth limit long periods of inactivity (>2h) during the waking hours (32).

The problems associated with self-reported measures of children's PA combined with the emergence of unobtrusive objective measures of PA (e.g., motion sensors) have enabled researchers to objectively examine the PA behaviors of school-aged youth. The accumulated evidence suggests that males are more physically active than females, and accumulated PA declines as children transition into adolescence (25,36,42,44). Using accelerometers, Trost etal. (44) and Thompson et al. (42) documented the decline in moderate and vigorous PA participation as youth move through childhood and into adolescence (Fig. 1). This pattern of PA decline supported previous research ADD using energy expenditure (36) (Fig. 2). In recent research using pedometers, Le Masurier et al. (25) illustrated the decline in PA as children moved into adolescence (Fig. 3). In each of these studies, the type of PA cannot be determined from the objective assessment tool. Therefore, measurement experts suggest a combination of objective and self-report measures to capture all dimensions of PA (i.e., frequency, intensity, duration, and type) (51). Direct observation techniques and self-report measures can determine the type of PA engaged in by youth, but the well-established limitations of these assessment tools (e.g., investigator burden, problems with children recalling PA) make these assessment tools unsuitable for collecting PA data with large samples over the entire youth age range (52). In addition, few youth self-report measures include questions about walking.

FIGURE 1
FIGURE 1:
Mean minutes of moderate-to-vigorous intensity PA of youth. Significantly different from previous grade group. *Significant (P< 0.05) gender difference within grade group. Based on data from Trost et al. (44).
FIGURE 2
FIGURE 2:
Total daily energy expenditure for females and males ages 6-18. Adapted from Rowland (36).
FIGURE 3
FIGURE 3:
Mean steps per day for female and male students by grade cluster. Significant sex by grade interaction (P < 0.001). Based on data from Le Masurier et al. (25).

Although there are limitations associated with the assessment of PA in youth, data do warrant several general conclusions. Regardless of the measurement technique used, activity levels decline from early childhood to late adolescence, and males are more active than females (14). The nature of activity patterns changes as well (Figs. 1-3). Based on the available data (37,43,44), it can be concluded that the majority of children and adolescents are meeting current PA guidelines and a higher percentage of boys meet the guidelines compared with girls. Data regarding extended periods of inactivity and walking are not available.

It could be argued that opportunities for walking among youth have diminished due to policies regarding transportation to and from school, advances in technology, and impact of the built environment, which may require youth to rely on vehicular transportation to access recreational facilities and perform purposeful activities of daily living (e.g., getting to and from school). Trends in adult walking behavior support this contention (7); however, until the walking behaviors of youth are directly assessed, this contention remains speculation.

WALKING BEHAVIORS OF OLDER ADULTS

Older adults (i.e., adults ages 65 and above) comprise the fastest growing age segment of the US population. In the year 2000, it was estimated that there were 35 million adults aged 65 yr or older in the United States, equating to approximately 12% of the total population, a figure that has been predicted to double by the year 2030 (47). This growth trajectory is projected for both older adults over the age of 65 and those over 85. Advanced age is associated with declining health, which affects older adults financially, physically, psychologically, and socially (8,29,34,48). This disproportionate burden is manifested by greater incidences of hospital stays and daily care, doctor visits, chronic health conditions, disability, and limitations in cognitive, physical, and psychosocial function (1). All of these outcomes have implications for quality of life in this increasingly aging society (26).

PA has emerged as an important mechanism for preventing and potentially reversing age-related declines in quality of life through its influence on three general areas of functioning: psychosocial, cognitive, and physical (Fig. 4). Despite the demonstrated health benefits and risk reductions associated with PA, only 36.3% of adults over 65 yr accumulate 30 min or more of light to moderate leisure-time physical activity (LTPA) on five or more days of the week as recommended by the Centers for Disease Control and Prevention and the American College of Sports Medicine (9,34). Although only 25% of older adults report walking on a regular basis, with many nonactive adults reporting lack of time as a barrier (17), walking represents one of the most accessible and prevalent modes of PA among older adults. That is, walking is a form of aerobic activity that most individuals, regardless of socioeconomic status, can perform across the lifespan. It is therefore unsurprising that walking is frequently used as an intervention technique in randomized controlled exercise trials. Moreover, the effects of this behavior on physical and psychological function are both significant and consistent.

FIGURE 4
FIGURE 4:
The role of PA as a determinant of health and well-being in older adults.

Many narrative reviews have highlighted the relationship between PA and psychological well-being in older adults (e.g., Ref. (28)). Likewise, a recent meta-analysis provides convincing quantitative support for this relationship. Netz etal. (33) identified multiple categories of psychological well-being. More than half the studies included multigroup designs, although study designs did not allow for estimation of PA effects by intensity, minimum time, or specific mode. There was a significant overall effect (ES = 0.19) for PA on psychological well-being with consistently greater improvements in activity conditions than controls. Additionally, there were significantly greater effects for PA conditions versus controls for overall well-being, self-efficacy, view of self, and anxiety (Fig. 5). Aerobic training demonstrated a slightly stronger influence on psychological well-being than resistance training, although this difference was not significant. Additionally, moderate-intensity activity had a stronger effect on well-being than light- or vigorous-intensity activity. Given the current health guidelines, this latter finding appears particularly important. Future research should be directed at examining potential dose-response effects and thresholds of PA dose for psychological well-being.

FIGURE 5
FIGURE 5:
Mean effects of PA on multiple dimensions of psychological well-being (Ref. (33)). *P < 0.05 difference between mean effect for treatment samples. PWB indicates psychological well-being.

Cognitive declines have been accepted as an almost universal consequence of the aging process. However, recent evidence suggests that regular PA may be able to slow or potentially reverse such declines. McAuley et al. (27) have noted that early studies of the fitness and cognitive function relationship were methodologically and theoretically limited. A recent meta-analysis by Colcombe and Kramer (10) examined the fitness and cognition relationship in randomized control trials. Their findings suggest that aerobic fitness training programs have a particularly robust effect on executive control function (Fig. 6). Declines in executive control function (i.e., planning, scheduling, coordination, etc.) have been reliably associated with the aging process (53). Advances in measurement technology have also allowed for more accurate assessments of the neuroanatomical structures responsible for cognitive improvements after exercise. For example, using functional magnetic resonance imaging (fMRI) and voxel-based morphological analyses, changes in cognition resulting from cardiovascular fitness training have been shown to manifest as differential activation of the prefrontal, parietal, and temporal cortices (12). Additionally, older and fitter adults have been shown to have greater sparing of cortical tissue than their sedentary counterparts (11). Therefore, tasks assessing executive control function coupled with complex, noninvasive imaging techniques (e.g., fMRI, positron emission tomography, and optical imaging) may constitute the most appropriate approach to assessing changes in brain structure and function associated with PA interventions in older adults.

FIGURE 6
FIGURE 6:
Effect sizes for the different process-task types reflecting the four theoretical hypotheses concerning the process-based specificity of the benefits of fitness training. Parenthetical notations on the x-axis indicate the number of effect sizes contributing to the point estimates for each task type in the exercise (E) and nonexercise (C) groups. Error bars show standard errors (Ref. (10)).

Physical function is also susceptible to declines with aging but may be afforded a protective effect through PA. A recent review by Keysor (24) concluded that PA, particularly walking, can reduce functional limitations in older adults. For example, as little as one mile of walking per week was demonstrated to be effective in slowing the progression of functional limitations (31). However, the measurement of and conceptual distinctions among functional performance, functional limitations, and disability are challenges that remain to be resolved. Nagi's disability framework (1965, 1991) has been proposed as a useful conceptual framework for distinguishing and measuring these constructs (20,24). Until there is consistency in these objectives, it remains difficult to synthesize the findings of studies examining the PA and the functional limitations and disability relationship (20).

PA is proposed to influence quality of life in older adults through its effect on psychological, cognitive, and physical function. Although current research supports these relationships, challenges in measurement across all three domains need to be addressed. For example, psychological health can be measured in many ways (e.g., anxiety, depression, positive affect), but more encompassing measures of psychological well-being may prove more effective as mediators of the PA and the quality of life relationship. Likewise, executive control tasks in combination with advanced imaging techniques (e.g., fMRI) promise to be most informative in assessing PA-related changes in cognitive function. Finally, measurement of physical function is best accomplished when delineating this domain into functional performance, perceived limitations, and disability and assessing these constructs using a combination of objective (i.e., behavioral) and subjective (i.e., self-report) techniques. Developing consistency with respect to the conceptualization and measurement of psychosocial, cognitive, and physical function will aid in our understanding of how PA influences quality of life in older populations.

WALKING BEHAVIORS IN INDIVIDUALS WITH DISABILITIES

For individuals with chronic disease or disability, a critical restriction in the activities of daily living pertains to ambulation. Expected health benefits that would result from PA for this part of the population remain largely unassessed. In some areas, such as mental retardation, reviews of PA behaviors are beginning to emerge (40). The costs to the individual as well as to society for locomotor-related disabilities are substantial, and interventions to address ambulation and mobility issues are warranted (16).

The identification of variables that are the most relevant to ambulatory status should take into account the pathophysiology, impairment, and functional limitations that are prominent features of a particular disease or disabling condition (16). For example, in the instance of Parkinson disease, the pathophysiology is dopaminergic degeneration in the basal ganglia, leading to impairments in the form of rigidity and tremor. Functional limitations arising from these impairments are slow and unstable walking patterns. Much of the research in motor control that has assessed ambulatory status has focused on variables such as walking speed, step length, frequency, and variability. In the following sections, the relevance and the limitations of these variables for PA assessment, clinical diagnosis, and rehabilitation will be reviewed.

Research on walking behaviors in individuals with disabilities has consistently shown a reduction of walking speed as well as decreased stride length (e.g., Refs. (18,22); Fig. 7). Another key finding is that with various pathologies, the variability of stride interval and stride length increases (Fig. 7). Increases in variability of stride variables are also associated with different degrees of severity within a disease, such as the presence of freezing in patients with Parkinson disease. These increases in stride-to-stride temporal and spatial variability have been associated with increased risks of falling. Although this association between stride variability and fall risk may be very important for clinical diagnosis, a full understanding of the changes in walking stability and adaptability (i.e., the target of rehabilitation and intervention strategies) will only be obtained through assessment of the coordinative changes of gait patterns. Stride parameter changes as well as their variability clearly are a reflection of coordinative aspects between muscles, segments, and joints throughout the body.

FIGURE 7
FIGURE 7:
Left panel: speed (m·s−1) and stride length (m) differences between a group with Parkinson disease and a healthy control group. Right panel: variability of stride interval (%) for both groups. Data adapted from Frenkel-Toledo et al. (18).

In many studies, walking behaviors of participants from different age groups or healthy control and disease groups have been assessed at preferred gait speed. It is well known that preferred speed changes with age and disease, and it has been shown that the variability of stride parameters changes with movement speed (50). In many studies that have demonstrated a change in stride parameters or an increase in variability with disability, there is a potential confounder in that these assessments were made at different movement speeds. Therefore, a limitation of much of the research that has demonstrated a correlation between stride variability and risk for falling or instability is the lack of control for movement speed.

In the dynamic and complex systems approaches to movement rehabilitation (e.g., Ref. (38)), an essential focus is the processes of coordination change and the stability of movement patterns. A critical aspect in these approaches is the identification of so-called control parameters, whose manipulation will reveal the full range of possible movement coordination patterns that can be exhibited. Coordination in human movement involves the integration of multiple degrees of freedom (such as joints, limb segments, and muscles) into coherent functional units. In locomotion research, the manipulation of movement speed, a highly controlled parameter, has revealed the stability aspects of walking and running in humans and the multiple coordinative patterns during walking when upper and lower body movements are taken into account (e.g., Ref. (49)).

Coordination between trunk and pelvis has been identified as a major determinant for postural stability during walking (49). Systematic manipulation from very low to high walking speeds has shown that in healthy young individuals, this coordination changes from mostly synchronized movement (pelvis and trunk are "in-phase": they move in the same direction) to a countermovement ("out-of-phase": pelvis and trunk move in opposite directions). This change of coordination is necessary to maintain a stable gait (such as not falling down) at higher walking velocities. In older individuals, there is less change in coordination to an out-of-phase pattern at higher speeds (49). In persons with recently diagnosed as well as more advanced Parkinson disease, there is significant further reduction in this countermovement and required changes in coordination when movement speed is increased (Fig. 8A). Similar synchronized movements have been found in the coordination between trunk and head during walking.

FIGURE 8
FIGURE 8:
(A) Change in coordination (relative phase) between pelvis and trunk for a group of recently diagnosed Parkinson disease (PD) and control group (CO) as a result of walking speed manipulation. PD group shows less overall change in relative phase with speed. (B) PD group has reduced variability from stride to stride compared with control group. (C) No differences in stride duration variability were observed between groups. Data adapted from Van Emmerik et al. (50).

Importantly, older individuals have been shown to compensate for these coordinative changes in the movements of the trunk and the pelvis through increased arm movement. As rigidity and lack of arm movements are critical symptoms of people with Parkinson disease, this lack of coordinative adaptations in the upper body will likely play a critical role in gait instability in this disease. In addition, the disability-related changes in upper body coordination will also impact visual perception, as trunk and head movements are important in orienting to central and peripheral visual information.

More recent research on locomotion from the perspective of nonlinear dynamics and complex systems has examined the nature of variability in stride intervals (see Ref. (22)). Stride interval time series obtained over long periods of over ground locomotion contain self-similar fractal structure with long-range (1/f-type) correlations. In contrast to random fluctuations, these 1/f or self-similar fluctuations represent a more adaptive system. These stride-to-stride fluctuations appeared more random in the gait of individuals with Huntington and Parkinson disease. Although the notion that different forms of variability (more random versus more structured 1/f type self-similar noise) could distinguish healthy from pathological gait might hold important clues for identification of pathologies, the link to gait stability is at best incomplete at present.

The coordination analyses related to the upper body discussed earlier also revealed that the variability of the coordination between pelvis and trunk, as measured by the between cycle variation in their coupling, changes systematically with aging and disease (49,50). People with Parkinson disease demonstrate significant decreases in this coordinative variability compared with healthy age-matched controls (Fig. 8B). This reduced variability may be associated with the overall rigidity and the inability to transition between different patterns. These findings are in agreement with the recent shift in focus on variability as playing a more functional role in pattern formation in biological systems (19).

Chronic disability and illness have a serious impact on people's mobility and physical status. PA assessment and promotion have the potential to significantly improve overall health and mobility in this part of the population. For people with disability, exercise and PA prescriptions should place more emphasis on clinical status and abilities. As a result, exercise mode, frequency, and intensity should be modified according to clinical condition. The research described here aimed to identify the critical variables associated with assessing an individual's walking behavior. Traditional stride parameters such as walking speed, stride length, and frequency are important in determining walking ability and are relatively easy to assess. However, limitations in these variables were discussed, and a more in-depth coordination analysis of the upper and lower body was presented as a critical tool to determine changes in walking stability in chronic disease. Finally, this review also questioned the traditional association of greater variability in walking variables with unstable gait. Instead, the functional role of variability in the control of walking and its potential role in pattern change and adaptation were emphasized.

THE DESCRIPTIVE EPIDEMIOLOGY OF WALKING: AN INTERNATIONAL PERSPECTIVE

There are many ways in which humans walk for many different purposes. Typically, in epidemiological studies in developed countries, we have studied LTPA, which is for recreation or exercise, and examined its relationship to health outcomes (5). Within the domain of LTPA, walking is usually for the purpose of fitness or health benefit, but there are many other ways to walk. In populations in the developing world, LTPA may be lower in prevalence, and most of the ways in which people walk is utilitarian. This includes purposive walking for work, for the completion of domestic chores and home-based yard work, or for active commuting or transportation.

A few studies have examined the prevalence of walking behaviors. Most adults walk at least a small amount each day, but less than half the population are regular LTPA walkers in developed countries (4,18,30). However, there is some evidence for increases in LTPA walking (39). There are also educational gradients in leisure time walking, as evidenced in the US population (18), which are not necessarily present if other modes of walking were considered; the reverse gradient may be apparent in developing countries, with poor people walking more than the socioeconomically advantaged (21). A study conducted comparing leisure time walking and walking for active commuting in China (23) surveyed a random regional sample of 4000 adults of middle age and with mixed socioeconomic status. The study showed that approximately two-thirds of adults did no LTPA, but almost all reported some commuting- or transport-related walking (over 90%). These data suggest that there are different patterns of walking, and that different prevalence rates for total PA would be observed internationally, if one examined different domains of walking.

The measurement of PA is relevant in the context of increases in noncommunicable disease and the antecedent risk factors in developed and developing countries (55). The World Health Organization (WHO) now considers PA as an integral and strategic part of noncommunicable disease prevention and control (54). The implementation of the Global Strategy for Diet and Physical Activity requires attention to PA promoting strategies and also careful monitoring and surveillance systems to determine whether populations have changed their level of PA over time (5). This requires international PA monitoring systems that are comparable among countries and over time. The measurement of walking, across domains and settings, is an important part of PA assessment. Recent efforts have been made to develop such measures, through both scientists collaborating around this issue and through specific efforts of the WHO toward this end.

There have been two major efforts to develop international PA measurements for use in population surveillance over the past decade. These are the International Physical Activity Questionnaire (IPAQ) and the Global Physical Activity Questionnaire (GPAQ). The IPAQ questionnaire was developed by a group of collaborating PA researchers, starting with an expert meeting in WHO Headquarters Geneva in 1998. This group aimed to develop an internationally comparable PA instrument specifically for population surveillance. The first phase worked on developing questions that would have cross cultural comparability and included the development of both short and long forms of the IPAQ instrument. The short form measured walking, moderate-intensity activity, and vigorous-intensity activity as generic domains, and the long form had specific questions in each domain separately, asking about walking, moderate-intensity PA, and vigorous-intensity PA at work, at home, for transport, and for sport recreation or leisure. The IPAQ group undertook a reliability and validity study in 12 countries (15). In summary, the reliability of the short version averaged around Spearman rank correlation coefficient (ρ) = 0.76, and for the long IPAQ form ρ = 0.81. The intermethod comparison, assessing the long versus the short form, had a median ρ of 0.67 (15). In terms of validity, the IPAQ long and short forms showed only modest median correlations with accelerometer data, averaging around 0.3 for the short form and 0.33 for the long form. The conclusions from these studies confirmed that the reliability and validity properties were similar to other self-report LTPA instruments in developed countries, and because this IPAQ measure had been tested across countries and language groups, it was decided that, although the coefficients were still low, this was a reasonable and an acceptable measure for international population surveillance. The IPAQ measure and scoring protocol is available from www.ipaq.ki.se.

The final phase of the IPAQ work program was to conduct a pilot prevalence study in as many countries as could participate. All participating countries had to provide a representative population sample, with a sample size of around 1500 or more for each country. A protocol was standardized, data were collected at the same or comparable times of the year, and local organizers and researchers had to obtain funding for and conduct the study. Data were collected from 19 countries, of which half were developing or transitional countries. Data were collected between 2002 and 2004, with response rates typically between 50% and 60% for most countries.

Data specifically on walking demonstrated that in six countries walking contributed more than moderate and vigorous activity to total PA. Further exploration of the reasons behind this observation is in progress, but four of the six countries with high rates of walking were developing countries, suggesting that in those settings, population PA is greatly and substantively influenced by walking behavior.

Since around 2001, the WHO and its member nations have developed an alternative to the IPAQ instrument, which is the GPAQ (56). This instrument is domain specific but is intermediate in length between the IPAQ short-form generic questionnaire and the domain-specific IPAQ long-form questionnaire. GPAQ version 2 is 16 items long and has been tested in 10 developing countries (56); results suggested similar repeatability to IPAQ (ρ = 0.67 to 0.81) and similar criterion validity (here compared with pedometers, ρ = 0.31). GPAQ has questions on the work domain, active transport, and leisure or recreation time (2,56). It is currently recommended as the PA measure in the WHO STEPS cardiovascular surveillance program, which has been completed in many developing countries. Comparisons of walking data, by domain and by country, will be available when these data are analyzed and pooled.

In summary, recent innovations in physical activity (PA) assessment have made it possible to assess the walking behaviors of a wide variety of populations. To date, researchers examining youth PA have focused on patterns of PA, intensity of PA, and total PA rather than walking behaviors. Results of these studies indicate that children are more active than adolescents, and males are more active than females. However, statements about youth walking behavior cannot be made until direct assessments of walking are conducted. Conversely, the benefits associated with walking for older adults have been well documented, although improvements in the assessments of physical, cognitive, and psychosocial parameters must be made if we are to fully understand the benefits of walking for people of all ages. Walking research focused on people with disabilities has identified relevant biomechanical and neurophysiological variables that are the most relevant to ambulatory status. This line of research will continue to inform medical and health professionals working with people whose disabilities affect their walking behaviors. Finally, international collaborations have set the stage for the surveillance of PA and walking behaviors among people of the world. Initial findings demonstrate that people of the world walk in different ways. Nevertheless, walking is the most prevalent PA across the world and had the greatest potential across age groups, educational gradients, and cultural groupings to be influenced by health promotion strategies and interventions.

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    Keywords:

    WALKING; ACTIVITY PATTERNS; SPECIAL POPULATIONS

    ©2008The American College of Sports Medicine